Deploy protection across the entire RAG workflow in minutes. Remove security blockers that slow AI projects and enable trusted, compliant use of enterprise data from day one.
Source: Thales Cybersecurity Products
51 %
Enterprise AI systems that already use Retrieval-Augmented Generation (RAG), up from 31% in 2023.
80 %
Amount of unstructured data in most enterprises — exactly the kind of content RAG systems pull into LLMs.
34 %
Businesses that are running or testing AI have already suffered and AI-related breach.
Secure your data. Unlock your AI.
Key Capabilities
Secure RAG AI: Thales Data Protection
Thales Retrieval-Augmented Generative (RAG) AI Data Protection Solutions safeguard sensitive data across the RAG workflow.
Using CipherTrust Data Discovery and Classification, Transparent Encryption, Cloud Key Management, and Data Activity Monitoring, Thales secures vector databases, supports GDPR/HIPAA compliance, and reduces exposure, hallucinations, and unauthorized access.
Pre-Ingestion Discovery
Identify and classify sensitive data before ingestion using CipherTrust Data Discovery and Classification. Secure it via tokenization, encryption, or masking with the CipherTrust platform, aligning with enterprise policies to prevent unauthorized access from the start.
Transparent Encryption
CipherTrust Transparent Encryption (CTE) encrypts entire vector database storage transparently, allowing only authorized processes access. Ideal for self-managed databases, it requires no integration changes while protecting data at rest.
Cloud Key Management
CipherTrust Cloud Key Management (CCKM) handles encryption keys independently for SaaS vector databases. Compatible with services like AWS KMS External Key Store, it ensures secure key control separate from providers.
Activity Monitoring
Thales Data Activity Monitoring (DAM) provides real-time monitoring of RAG data interactions, using ML for behavioral baselining, anomaly detection, and automated alerts. Supports compliance reporting for regulations like HIPAA across hybrid environments.
End-to-End Resilience
Build compliant RAG systems with vulnerability assessments, least-privilege enforcement, and integration across the lifecycle. Minimize risks from misconfigurations or over-privileged accounts, enabling secure AI adoption for competitive advantage.
Resources
| Image | Title | Link |
|---|---|---|
 | Solution Brief: Thales Retrieval Augmented Generative (RAG) AI Data Protection Solutions |
Frequently Asked Questions
How does this protect RAG data?
The solution secures every stage of a RAG pipeline. It discovers and classifies sensitive data before ingestion, encrypts documents and vector embeddings at rest, keeps encryption keys under your control, and monitors access to detect misuse or policy violations.
Can we use it with SaaS vector databases?
Yes. It works with both self-managed and SaaS vector databases. You can keep keys in your own HSM or cloud KMS while the provider stores only encrypted data. This lets you adopt managed RAG services without losing control over secrets or compliance posture.
Will this slow down our RAG apps?
It’s designed to minimize performance impact. Encryption is applied at the storage and key-management layers, so applications and RAG logic usually require little to no change. You can selectively encrypt the most sensitive datasets to balance security with latency and query throughput.
How does it support compliance needs?
The solution helps enforce policies aligned with GDPR, HIPAA, PCI DSS and other frameworks. It discovers and classifies regulated data, applies strong encryption and key control, and produces detailed access and activity logs so you can prove how sensitive data is protected, accessed, and retained in your RAG environment.
What is required to get started?
You integrate the platform with your existing data stores, vector database, and cloud KMS, then run discovery to locate sensitive data. From there you define protection policies (masking, tokenization, encryption) and enable monitoring so every RAG query and data access is governed and auditable.